The AI economy is real, substantial and growing three times faster than the internet, mobile phone or cloud computing. But is it sustainable?

Our forensic analysis from June of this year of 1,000+ companies reveals that over $70 billion in revenue is coming from Main Street enterprise adoption, rather than loss-making labs or VC-funded startups.

However, we’re still in the foothills: even as models get cheaper, corporate bills keep rising; and hyperscalers are only just covering the costs of the data center buildout, with margins still years away. In this Q&A about the state of the AI economy, I discuss:

00:00 The AI economy is real
00:35 Who’s really paying for AI, and how we checked
02:53 Will AI infrastructure spending pay off?
04:36 Creating a “Brent crude” for tokens
05:47 Cheaper models, bigger bills
06:38 What AI leaders spend per employee, and why it matters
07:38 When a cheap open-source model is all you need
08:30 Congestion: the biggest problem CEOs hit with AI
09:49 What life looks like when intelligence is cheap
10:54 Why it doesn’t matter who wins the AI race
12:04 Is AI really making us stupid?
13:24 China’s efficiency moat

Note: this was recorded before our latest tracker update and the annualized run rate has since grown to $229 billion. For an updated measure of the AI economy, see sources below.

📄 Full report: https://intelligence.exponentialview.co/
📈 The latest revenue figure: https://www.investmentbrief.ai/p/ai-investment-brief-monday-3

About Exponential View:
Welcome to Exponential View, where Azeem Azhar examines how exponential technologies such as AI are reshaping the future. Each week, Azeem shares his analysis or speaks with an expert guest to shed light on frontier shifts across technology, business and society.

To keep up with the Exponential transition, subscribe to this channel or the newsletter: https://www.exponentialview.co/
To keep up with our AI economy research, subscribe to https://www.investmentbrief.ai/

Where to find me:

Exponential View newsletter: https://www.exponentialview.co/
Website: https://www.azeemazhar.com/
LinkedIn: https://www.linkedin.com/in/azeem/
Twitter/X: https://x.com/azeem

Production by EPIIPLUS1.
Production and research: Baba Films, Marija Gavrilov.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years.

Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.

To keep up with the Exponential transition, subscribe to this channel or to my newsletter:

https://www.exponentialview.co/
—
More than three years after ChatGPT's release, only 27% of executives say AI has met their ROI expectations. The history of factory electrification explains why — most companies are at the light-bulb stage, adding Copilot licenses rather than reconceptualizing their businesses around AI. In this episode I map the three stages of AI adoption, and show what it actually takes to move from chatbots to the autonomous company — the only stage where the moat becomes real.

I covered:

(01:40) Ford's electricity playbook: why AI adoption needs a complete rethink

(03:51) The congestion problem: why AI gains stall

(05:45) Chatbot to autonomous company: your three-stage roadmap

(06:40) Why individual productivity gains won't build a moat — and what will

(10:17) Which companies are getting AI transformation right

(14:12) My 2029 AI adoption forecast — and how to stay ahead

Read my essay "Why AI isn't showing up on your bottom line" on Substack: https://www.exponentialview.co/p/why-ai-isnt-showing-up-on-your-bottom-line
—
Where to find me:

Exponential View newsletter: https://www.exponentialview.co/

Website: https://www.azeemazhar.com/

LinkedIn: https://www.linkedin.com/in/azeem/

Twitter/X: https://x.com/azeem

Production by EPIIPLUS1.

Production and research: Baba Films, Chantal Smith, Marija Gavrilov.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years.

Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.

To keep up with the Exponential transition, subscribe to this channel or to my newsletter:
https://www.exponentialview.co/

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Published in early March 2026, Andrej Karpathy's autoresearch AI tool makes autonomous scientific experimentation cheap and easy — but it was designed to solve machine learning problems. I wanted to see if I could apply its loop architecture to my own work: refining my worldview, testing arguments, solving business problems. In this video, I share how I adapted Karpathy’s autoresearch loops for problems that aren't easy to quantify, how to avoid the local minima trap, and the broader impact of these kinds of methods. I covered:

(02:11) The Karpathy Loop: what is it and how does it work
(07:54) Extending the loop into business and thinking
(09:46) The local minima trap
(12:20) The escape harness: getting beyond “good enough”
(16:05) What I’ve learned after 30 days
(18:47) The loop economy: from doing to judging

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Where to find me:

Exponential View newsletter: https://www.exponentialview.co/
Website: https://www.azeemazhar.com/
LinkedIn: https://www.linkedin.com/in/azeem/
Twitter/X: https://x.com/azeem

Production by EPIIPLUS1.
Production and research: Baba Films, Chantal Smith, Marija Gavrilov.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.